///<summary>Выполняет прямой проход через декодирующую нейросеть.</summary>
///<param name="input">Входные данные.</param>
public Tensor Decode(Tensor Content, Tensor[] Styles)
{
var Temp = Layers.StyleDecorator(Content, Styles[3]);
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv4_1_Weights, this.Data.Conv4_1_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Upsample2D(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_4_Weights, this.Data.Conv3_4_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_3_Weights, this.Data.Conv3_3_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_2_Weights, this.Data.Conv3_2_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.AdaIN(Temp, Styles[2]);
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv3_1_Weights, this.Data.Conv3_1_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Upsample2D(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv2_2_Weights, this.Data.Conv2_2_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.AdaIN(Temp, Styles[1]);
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv2_1_Weights, this.Data.Conv2_1_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Upsample2D(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv1_2_Weights, this.Data.Conv1_2_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.AdaIN(Temp, Styles[0]);
Temp = Layers.Conv2D3x3(Temp, this.Data.Conv1_1_Weights, this.Data.Conv1_1_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.ReLU(Temp);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
Temp = Layers.Conv2D7x7(Temp, this.Data.Conv_Out_Weights, this.Data.Conv_Out_Biases);
if (this.Step != null)
{
this.Step(1f / 22f * 100f);
}
return(Temp);
}
